expcondinv

This function computes the inverse conditional expecatation for a given copula family and a given margin variables for a clustered data model. The clusters ar3e independent but the observations with clusters are dependent, according to a one-factor copula model.

Estimation of 2-level factor copula-based regression models  for clustered data where the response variable can be either discrete or continuous.

Bruno Remillard

CopulaGAMM

Copula-Based Mixed Regression Models

Pavel Krupskii

expcondinv function

<dl><dt>u</dt>
<dd>conditional expectation</dd>
<dt>family</dt>
<dd>copula model: "gaussian" , "t" , "clayton" "joe", "frank" , "gumbel", "plackett"</dd>
<dt>cpar</dt>
<dd>copula parameter</dd>
<dt>rot</dt>
<dd>rotation: 0 (default), 90, 180 (survival), or 270</dd>
<dt>margin</dt>
<dd>marginal distribution function of the response</dd>
<dt>subs</dt>
<dd>number of subdivisions for the integrals (default=1000)</dd>
<dt>eps</dt>
<dd>precision required</dd></dl>

Arguments

Pavel Krupskii and Bruno N. Remillard

Author

Inverse conditional expectation for a vector of probabilities — expcondinv

<dl>

<dt>u</dt>
<dd>conditional expectation</dd>


<dt>family</dt>
<dd>copula model: "gaussian" , "t" , "clayton" "joe", "frank" , "gumbel", "plackett"</dd>


<dt>cpar</dt>
<dd>copula parameter</dd>


<dt>rot</dt>
<dd>rotation: 0 (default), 90, 180 (survival), or 270</dd>


<dt>margin</dt>
<dd>marginal distribution function of the response</dd>


<dt>subs</dt>
<dd>number of subdivisions for the integrals (default=1000)</dd>


<dt>eps</dt>
<dd>precision required</dd>

</dl>

expcondinv: Inverse conditional expectation for a vector of probabilities

Description

Usage

Value

Arguments

Author